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Dataset Partition Sizes — Category Frequencies + Daily Sum Series
x402
Dataset Partition Sizes — Category Frequencies + Daily Sum Series is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-19).
Analyzes dataset partition size records (row_count, file_mb) to produce category frequency counts by group and a daily sum time series, delivered as two independent analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Dataset partition sizes — Category frequencies + Daily sum series: Category frequencies + Daily sum series for supplied dataset partition sizes records (row_count, file_mb). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 rows.
Output
Returns two analytical reports: (1) a category frequency table showing how many records exist per dataset_group value, and (2) a daily sum time series aggregating the selected numeric field (row_count or file_mb) by date. Up to 200 rows of input are processed locally with no external calls.
Example use cases
Monitor partition growth by group
“I have a list of dataset partition records with dates, group names, and row counts — can you tell me how frequently each group appears and what the total row_count looks like day by day? Here's the data for the past week across groups alpha, beta, and gamma.”
Audit daily file size trends
“Can you run an analysis on these partition size logs and show me the daily sum of file_mb over time plus how many records each dataset_group has? I want to track if any group is ballooning in file size. Use file_mb as the measurement field.”
Validate dataset group distribution
“I've got about 150 rows of partition metadata with dataset_group, date, row_count, and file_mb fields — can you give me a frequency breakdown by category and a day-by-day sum series for row_count so I can see which groups dominate and whether row counts are growing?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-07-102?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have structured dataset partition records with group labels and dates and need both a categorical frequency distribution and a daily aggregated time series in a single $0.01 call. Ideal for data engineers monitoring ETL pipeline outputs, storage audits, or dataset growth tracking. Prefer this over general analytics tools when you need a lightweight, fast, offline-style dual-report with no external data access.
Side effects
- Input array exceeds 200 rows — request will be rejected or truncated
- Missing required fields (row_id, dataset_group, date, row_count, file_mb) cause validation errors
- Dates not matching YYYY-MM-DD pattern fail schema validation
- Numeric fields outside allowed range trigger boundary errors
- Empty rows array returns no results
- Invalid enum value for 'field' parameter (must be row_count or file_mb)
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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